1. Field of the Invention
The present invention relates to integrated circuit fabrication. More specifically, the present invention relates to a method and apparatus for rapidly assessing the quality of a process model for a mask layout using simulation.
2. Related Art
Dramatic improvements in semiconductor integration circuit (IC) technology presently make it possible to integrate tens of millions of transistors onto a single semiconductor IC chip. These improvements in integration densities have been achieved through corresponding improvements in semiconductor manufacturing technologies. In particular, advances in optical lithography technology have been driving IC chip feature sizes into deep submicron ranges, with the help of Optical Proximity Correction (OPC) techniques.
Model-based OPC techniques typically use a process model to correct a given layout. The process model allows the OPC technique to simulate the effects of one or more semiconductor manufacturing processes, which enables the OPC technique to ensure that the corrections made to the layout will result in an IC chip with the desired characteristics. Note that, in order for an OPC technique to be effective, it is very important that the process model accurately predict corrections for all pattern configurations encountered in a target layout, most of which might be different from those pattern configurations used for fitting the process model. Therefore, it is desirable to evaluate the quality of the process model on any given layout.
Unfortunately, current techniques for assessing the quality of a process model have many drawbacks. The best-known techniques for determining the quality of a process model are to determine how well they predict an empirically measured data set (i.e. process data), wherein the process data is taken on pattern configurations not used for model calibration. These measurement-based techniques are effective in helping to determine the quality of a model, but are limited by processing and data collection time. Because the gathering of process data is labor-intensive and time-consuming, the model is assessed using a small number of test patterns, which severely limits the accuracy of the assessment process due to the small sample size. So it is impossible to guarantee a model's predictive capabilities on all test patterns with these techniques. Additionally, measurement-based techniques have difficulty determining if an inaccuracy in the model is the result of errors in data collection or the model itself.
Hence, what is needed is a method and an apparatus for rapidly assessing the quality of a process model without the above-described problems.